Data Engineer Training Toronto

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Data Engineer Courses

Data Engineer Training Courses

Data Literacy and Tools Overview Training

Course ID: TP3152
Delivery: On-Site or Instructor-led Virtual
This course will provide participants with an introduction to key terms and important concepts related to data literacy.  Additionally, it will provide a brief overview of the core …

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Introduction to Talend Training

Course ID: TP2700
Delivery: On-Site or Instructor-led Virtual
This 3 day course provides an introduction to Talend.

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Cloud Data Engineering with NiFi on AWS or GCP Training

Course ID: TP2913
Delivery: On-Site or Instructor-led Virtual
This course is intended for students looking to learn data processing on the cloud with Apache NiFi – a visually programmed software tool that automates the movement and transformation of …

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Data Science and Data Engineering for Architects Training

Course ID: WA3057
Delivery: On-Site or Instructor-led Virtual
This intensive training course covers the theoretical and practical aspects of applying the principles and methods of Data Science and Data Engineering in practice.  The students are …

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API Management Fundamentals for Architects Training

Course ID: WA2895
Delivery: On-Site or Instructor-led Virtual
Does your organization want to expose its internal system APIs for external or public consumption in a completely secure and controlled way? With this API management course designed …

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Workflow Management with Apache Airflow Training

Course ID: WA3001
Delivery: On-Site or Instructor-led Virtual
Apache Airflow is a configuration-as-code OSS solution for workflow automation that is positioned as a replacement of cron-like scheduling systems.
Written in Python, Airflow enables …

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Proven Results

For over 20 years, we have trained thousands of developers at some of the country’s largest tech companies – including many Fortune 500 companies. We’re proudly distinguished by these clients, partners and awards.

aws training   Microsoft Silver Partner   ISACA logo   open group profit100

Reviews from past students who completed our Data Engineering Courses:

This was a great course. I loved the blend of Python Concepts Plus Just enough Data science to be productive
Instructor was very thorough, yet practical. He was a great communicator and explained everything in layman’s terms.
Great tutorials! I will go back to these
This course is excellent. It gave me an overview of data science and a good understanding. It put me in the right direction of data analysis in my work.

Should I Attend Data Engineer Training Toronto?

The data engineering field is expected to continue growing rapidly over the next several years, and there’s huge demand for data engineers across industries.

The global Big Data and data engineering services market is expected to grow at a CAGR of 31.3 percent by 2025.

Comprehensive data engineer training with Web Age will teach you to organize, analyze and interpret your many sources of big data and information.

The data engineer training courses we offer provide your teams the skills they need to discover insights required for analyzing and tackling critical factors such as risk, performance, quality, forecasting, estimating, simulation, business process improvement, and much more.

Data Engineer Training Toronto!

A global city, Toronto is a center of business, finance, arts, and culture, and is recognized as one of the most multicultural and cosmopolitan cities in the world.

Toronto is quickly becoming one of the largest tech hubs in Canada, supporting the vision city officials have of Toronto as the next ‘Silicon Valley North’. Working in Toronto is a great career choice – especially in the IT and communications sectors.

Web Age Data Engineering Courses are taught at locations throughout Ontario and Quebec venues. Our Toronto Data Engineer Training classes are delivered in traditional classroom style format. Online Data Engineering courses are also available in a synchronous instructor led format.

PySpark for Data Engineering & Machine Learning

In this Data Engineer Training video  we will review the core capabilities of PySpark as well as PySpark’s areas of specialization in data engineering, ETL, and Machine Learning use cases.

Frequently Asked Questions

What is a Data Engineer?

A data engineer conceives, builds and maintains the data infrastructure that holds your enterprise’s advanced analytics capacities together.

A data engineer is responsible for building and maintaining the data architecture of a data science project. Data Engineers are responsible for the creation and maintenance of analytics infrastructure that enables almost every other function in the data world. They are responsible for the development, construction, maintenance and testing of architectures, such as databases and large-scale processing systems. As part of this, Data Engineers are also responsible for the creation of data set processes used in modeling, mining, acquisition, and verification.

What is Data Engineering

Data engineering is a software engineering practice with a focus on design, development, and productionizing of data processing systems. Data processing includes all the practical aspects of data handling, including:Data acquisition, transfer, transformation, and storage on-prem or in the cloud. In many cases, data can be categorized as Big Data.

Gartner’s Definition of Big Data

Gartner’s analyst Doug Laney defined three dimensions to data growth challenges: increasing volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources).

In 2012, Gartner updated its definition as follows: “Big data are high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.”


Data sizes accumulated in many organizations come to hundreds of terabytes, approaching the petabyte levels.


Big Data comes in different formats as well as unformatted (unstructured) and various types like text, audio, voice, VoIP, images, video, e-mails, web traffic log files entries, sensor byte streams, etc.


High traffic on-line banking web site can generate hundreds of TPS (transactions per second) each of which may be required to be subjected to fraud detection analysis in real or near-real time.

What are the core Data Engineering skills?

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